Data Mining is the automatic search for interesting and useful relationships between attributes in databases. One major obstacle to effective Data Mining is the size and complexity of the target database, both in terms of the feature set and the sample set. While many Machine Learning algorithms have been applied to Data Mining applications. There has been particular interest in the use of Genetic Algorithms (GAs) for this purpose due to their success in large scale search and optimization problems. This par per explores how GAs are being used to improve the performance of Data Mining clustering and classification algorithms and examines strategies for improving these approaches.